CN111127284B

CN111127284B - Address selection method, recommendation method, device and storage medium for traffic stop sites

Info

Publication number: CN111127284B
Application number: CN201911097093.3A
Authority: CN
Inventors: 何墨
Original assignee: Alibaba Group Holding Ltd
Current assignee: Alibaba Group Holding Ltd
Priority date: 2019-11-11
Filing date: 2019-11-11
Publication date: 2023-06-20
Anticipated expiration: 2039-11-11
Also published as: CN111127284A

Abstract

The embodiment of the application provides a method, a device and a storage medium for selecting addresses of traffic stop sites, wherein the method comprises the following steps: acquiring a historical travel starting position and a historical travel ending position in a target traffic area; clustering the historical trip starting position and the historical trip ending position respectively to obtain at least one starting point cluster and at least one ending point cluster; and determining the position of the traffic stop in the target traffic area based on the at least one starting point cluster and the at least one ending point cluster. In the embodiment of the application, the travel behaviors of the crowd are analyzed in a clustering mode, so that the travel demands of the crowd can be accurately mined, the position of the traffic stop station is determined more flexibly and reasonably, and the convenience of traffic travel is improved.

Description

Address selection method, recommendation method, device and storage medium for traffic stop sites

Technical Field

The application relates to the technical field of intelligent transportation, in particular to a method, a method and equipment for recommending site selection of a transportation stop and a storage medium.

Background

With the continuous improvement of living standard, people's transportation travel mode becomes richer various. The bus travel not only can reduce the air pollution, but also can save a great amount of travel expenses, so that the bus travel becomes an indispensable travel mode in daily life of people.

At present, the site selection of the bus stop is usually carried out by relying on manual experience, however, the bus stop determined by the mode is unreasonable, and the travel requirements of people cannot be met.

Disclosure of Invention

Aspects of the application provide a method, a device and a storage medium for selecting a site for traffic stop, which are used for determining the position of the traffic stop more flexibly and reasonably and improving the convenience of traffic travel.

The embodiment of the application provides a method for selecting addresses of traffic stop sites, which comprises the following steps:

acquiring a historical travel starting position and a historical travel ending position in a target traffic area;

clustering the historical trip starting position and the historical trip ending position respectively to obtain at least one starting point cluster and at least one ending point cluster;

and determining the position of the traffic stop in the target traffic area based on the at least one starting point cluster and the at least one ending point cluster.

The embodiment of the application also provides a recommendation method of the traffic stop station, which comprises the following steps:

receiving a travel request sent by terminal equipment, wherein the travel request comprises a starting position and a termination position;

selecting a target transit stop station adapted to the start position and the end position from at least one transit station;

feeding back the target traffic stop to the terminal equipment;

the at least one traffic stop station is determined by clustering the historical trip starting position and the historical trip ending position respectively by the server.

responding to a travel configuration operation of a user, and generating a travel request, wherein the travel request comprises a starting position and a termination position;

the travel request is sent to a server, so that the server can select a target traffic stop station matched with the starting position and the ending position from at least one traffic station and feed back the target traffic stop station;

outputting the position of the target transportation stop fed back by the server;

Embodiments of the present application also provide a computing device including a memory and a processor;

the memory is used for storing one or more computer instructions;

the processor is coupled to the memory for executing the one or more computer instructions for:

Embodiments of the present application also provide a computing device including a memory, a communication component, and a processor;

the memory is used for storing one or more computer instructions;

the processor is coupled with the communication component and the memory for executing the one or more computer instructions for:

receiving a travel request sent by a terminal device through the communication component, wherein the travel request comprises a starting position and a termination position;

Feeding back the target transportation stop to the terminal equipment through the communication component;

The embodiment of the application also provides terminal equipment, which comprises a memory, a communication component and a processor;

the memory is used for storing one or more computer instructions;

the travel request is sent to a server through the communication component, so that the server can select a target traffic stop station matched with the starting position and the ending position from at least one traffic station and feed back the target traffic stop station;

Embodiments of the present application also provide a computer-readable storage medium storing computer instructions that, when executed by one or more processors, cause the one or more processors to perform the aforementioned method of locating or recommending a transit stop.

In the embodiment of the application, at least one starting point cluster and at least one ending point cluster can be obtained by respectively clustering the historical trip starting position and the historical trip ending position in the target traffic area; and determining a location of the transit stop within the target traffic zone based on the at least one start cluster and the at least one end cluster. Accordingly, in the embodiment of the application, the travel behaviors of the crowd are analyzed in a clustering mode, so that the travel demands of the crowd can be accurately mined, the position of the traffic stop station is determined more flexibly and reasonably, and the convenience of traffic travel is improved.

Drawings

The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute an undue limitation to the application. In the drawings:

FIG. 1a is a flow chart of a method for locating a stop according to an embodiment of the present disclosure;

fig. 1b is a schematic view of a service scenario provided in an embodiment of the present application;

FIG. 2 is a schematic diagram of an application area scope according to an embodiment of the present application;

FIG. 3 is a schematic diagram of a clustering result of a target traffic area according to an embodiment of the present disclosure;

FIG. 4 is a flowchart of a method for recommending a stop-stop station according to another embodiment of the present disclosure;

FIG. 5 is a flowchart of a method for recommending a stop-stop station according to another embodiment of the present disclosure;

FIG. 6 is a schematic diagram of a computing device according to another embodiment of the present application;

FIG. 7 is a schematic diagram of another computing device according to a further embodiment of the present application;

fig. 8 is a schematic structural diagram of a terminal device according to another embodiment of the present application.

Detailed Description

For the purposes, technical solutions and advantages of the present application, the technical solutions of the present application will be clearly and completely described below with reference to specific embodiments of the present application and corresponding drawings. It will be apparent that the described embodiments are only some, but not all, of the embodiments of the present application. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are within the scope of the present disclosure.

At present, a traffic stop station is usually established by experience, but the determined traffic stop station is unreasonable, and the travel requirements of people cannot be met. To ameliorate the problems of the prior art, some embodiments of the present application: by clustering the historical trip starting position and the historical trip ending position in the target traffic area respectively, at least one starting point cluster and at least one ending point cluster can be obtained; and determining a location of the transit stop within the target traffic zone based on the at least one start cluster and the at least one end cluster. Accordingly, in the embodiment of the application, the travel behaviors of the crowd are analyzed in a clustering mode, so that the travel demands of the crowd can be accurately mined, the position of the traffic stop station is determined more flexibly and reasonably, and the convenience of traffic travel is improved.

The following describes in detail the technical solutions provided by the embodiments of the present application with reference to the accompanying drawings.

Fig. 1a is a method for locating a stop according to an embodiment of the present application. As shown in fig. 1a, the method comprises:

100. acquiring a historical travel starting position and a historical travel ending position in a target traffic area;

101. Clustering the historical trip starting position and the historical trip ending position respectively to obtain at least one starting point cluster and at least one ending point cluster;

102. the location of the transit stop within the target traffic zone is determined based on the at least one start cluster and the at least one end cluster.

The method for selecting the address of the traffic stop station provided by the embodiment of the invention can be applied to various scenes in which the position of the traffic stop station needs to be determined, for example, can be used in a road network construction scene, a subway road network construction scene and other road network construction scenes sharing traffic, and the embodiment is not limited to the above. Based on the method for selecting the address of the traffic stop station provided by the embodiment of the application, the traffic stop station can be opened, deleted or the position of the traffic stop station can be modified in the application scenes, and the embodiment of the application is not limited to the method.

In addition, fig. 2 is a schematic diagram of an application area range provided in an embodiment of the present application. As shown in fig. 2, the method for locating a traffic stop provided in the embodiment of the present application may be applied to an environmental area to be analyzed, where the specification of the environmental area to be analyzed may be a district level, a city level, a provincial level, or the like, and of course, the embodiment is not limited thereto. The environmental area to be analyzed can comprise at least one traffic area, and the traffic area can be a custom area in the environmental area to be analyzed. In fig. 2, different traffic areas are characterized using different colors. For example, it may be an administrative area or the like within the environmental area to be analyzed, which is not limited in this embodiment.

In the following, a description will be given of a technical scheme taking a target traffic area in an environmental area to be analyzed as an example. It should be noted that the target traffic area may be any traffic area in the environment area to be analyzed, or may be a traffic area screened from the environment to be analyzed.

In this embodiment, the historical travel starting position and the historical travel ending position in the target traffic area can be obtained.

In some practical applications, the historical trip starting position and the historical trip ending position in the target traffic area can be obtained from trip record data corresponding to the environment area to be analyzed. The trip record data is used for recording the historical trip behaviors occurring in the environment area to be analyzed, and the trip record data can contain OD (origin-destination) information of the historical trip. Based on the OD information of the history trip, longitude and latitude information of each O, D point in the environment area to be analyzed can be obtained.

The travel record data may be travel data generated by a user using navigation software or taxi taking software, or may be residence information or job site information, and the source of the travel record data is not limited in this embodiment.

In addition, longitude and latitude information of the boundary of the target traffic area can be obtained. Based on the above, O, D points in the target traffic area can be determined based on the latitude and longitude information of each O, D point in the environment area to be analyzed and the latitude and longitude information of the boundary of the target traffic area. Accordingly, the historical trip start position and the historical trip end position in the target traffic area can be characterized by using the longitude and latitude information of O, D points in the target traffic area.

In other practical applications, the traffic area in the scene area to be analyzed can be used as a record range of the historical travel behaviors to generate travel record data in each traffic area, so that the historical travel starting position and the historical travel ending position in the target traffic area can be obtained from the travel record data corresponding to the target traffic area.

Of course, other implementation manners may be adopted in the embodiment to obtain the historical trip starting position and the historical trip ending position in the target traffic area, which is not limited in the embodiment.

In this embodiment, the historical trip start position and the historical trip end position in the target traffic area may be clustered respectively to obtain at least one start cluster and at least one end cluster.

That is, the historical trip starting positions in the target traffic area are clustered to obtain at least one starting point cluster; and clustering the historical trip ending positions in the target traffic area to obtain at least one end point cluster.

In this embodiment, the clustering manner may be selected according to the distribution characteristics of the historical trip starting position and the historical trip ending position in the target area. For example, if the distribution boundary of the historical trip starting positions in the target traffic area is relatively regular, the K-means algorithm may be used to cluster the historical trip starting positions in the target traffic area. For another example, if the distribution boundary of the historical trip ending positions in the target traffic area is not uniform, the historical trip ending positions in the target traffic area can be clustered by adopting a DBSCAN algorithm. For another example, if the distribution of the historical trip starting positions in the target traffic area is not uniform, the GMM algorithm may be used to cluster the historical trip starting positions in the target traffic area. Of course, these are merely examples, and the present embodiment is not limited thereto.

A clustering algorithm matched with the distribution characteristics of the historical trip starting position and the historical trip ending position in the target area can be adopted to obtain a better clustering effect. For example, the start and end clusters obtained using the K-mes algorithm are relatively diffuse, and the determined transit stops are relatively diffuse. For another example, the start point cluster and the end point cluster obtained by adopting the DBSCAN algorithm can exclude sporadic travel points far away from the area covered by the cluster. For another example, more clusters can be formed in areas where the historical travel starting location or the historical travel ending location is particularly dense using GMM algorithms.

Fig. 3 is a schematic diagram of a clustering result in a target traffic area according to an embodiment of the present application. After clustering, 7 clusters are generated in the target traffic area, as shown in FIG. 3, with different clusters labeled with different colors in FIG. 3. In addition, in fig. 3, the start cluster and the end cluster are not labeled, and in practical application, each cluster may be defined as a start cluster or an end cluster by setting IDs for the clusters and labeling the cluster types corresponding to the IDs.

The location of the transit stop within the target traffic zone may be determined based on the at least one start cluster and the at least one end cluster determined within the target traffic zone.

In this embodiment, a traffic stop departure station in the target traffic area may be determined according to at least one starting point cluster; and determining that the traffic stops in the target traffic area reach the station according to the at least one end point cluster. Accordingly, in this embodiment, at least two types of traffic stop stations, that is, a traffic stop departure station and a traffic stop arrival station, are available.

The technical solution for determining a stop-and-go departure point in a target traffic area will be described below by taking a first cluster of at least one start cluster as an example, wherein the first cluster is any cluster of the at least one start cluster.

If the known traffic stop stations exist in the coverage area of the first cluster, one of the known traffic stop stations can be selected as a traffic stop departure station in the coverage area of the first cluster.

If a plurality of known traffic stop stations exist in the coverage area of the first cluster, the known traffic stop station closest to the cluster center is taken as the traffic stop departure station of the coverage area of the first cluster; and if one traffic stop station exists in the coverage area of the first cluster, taking the known traffic stop station as a traffic stop departure station in the coverage area of the first cluster.

If the known traffic stop stations do not exist in the area covered by the first cluster, the traffic stop departure station of the area covered by the first cluster can be determined according to the cluster center of the first cluster. For example, a transit stop departure station may be set up at its cluster center location; alternatively, the known transit stop closest to the center of its cluster is taken as the transit stop departure stop within the area covered by the first cluster.

The technical solution of determining the arrival of a traffic stop in a target traffic area will be described below by taking a second cluster of the at least one end cluster as an example, wherein the second cluster is any cluster of the at least one end cluster.

If the known traffic stop stations exist in the area covered by the second cluster, one of the known traffic stop stations can be selected as the traffic stop arrival station of the area covered by the second cluster.

If a plurality of known traffic stop stations exist in the coverage area of the second cluster, the known traffic stop station closest to the cluster center is taken as the traffic stop arrival station of the coverage area of the second cluster; and if one traffic stop station exists in the coverage area of the second cluster, taking the known traffic stop station as a traffic stop arrival station of the coverage area of the second cluster.

If the known traffic stop station does not exist in the area covered by the second cluster, determining that the traffic stop of the area covered by the second cluster reaches the station according to the cluster center of the second cluster. For example, a transit stop arrival site may be set up at its cluster center location; alternatively, the known transit stop closest to the center of its cluster is taken as the transit stop arrival stop within the coverage area of the second cluster.

In this embodiment, the known traffic stop may be an existing bus stop, a subway stop or other stops already constructed for traffic stop, which is not limited in this embodiment.

Of course, in this embodiment, the categories of the traffic stop stations may not be distinguished, and this embodiment is not particularly limited thereto.

In addition, in the embodiment, the historical travel starting position and the historical travel ending position in at least one traffic area in the environment area to be analyzed can be visually displayed, and the starting point cluster, the ending point cluster, the traffic stop stations and the like related in the text can be visually displayed, so that part or all of the information can be provided for traffic fitters, travel crowds and the like more intuitively.

Fig. 1b is a schematic diagram of a service scenario according to an embodiment of the present application. Referring to fig. 1b, on the basis of determining a stop in a target traffic area based on the stop locating scheme provided in the present embodiment, a user may input a riding demand through his terminal device, such as the start point and the end point in fig. 1 b. In this embodiment, a stop station closest to the start point input by the user, such as a station a in fig. 1b, may be selected from stop stations in the target traffic area, and the station a is issued to the terminal device of the user. In addition, the path from the starting point input by the user to the site A can be issued to the terminal equipment of the user for reference by the user.

In addition, only the application interface for the origin of the user input is shown in fig. 1 b. For the destination of the user input, in this embodiment, a stop closest to the destination of the user input may also be selected from the stop in the target traffic area, for example, stop B (not shown in fig. 1B), and may be issued to the user's equipment terminal, for example, "please get off at stop B" may be prompted in the user equipment terminal, and in addition, a path from stop B to the destination (a building) may be issued to the user's terminal equipment for reference by the user.

Accordingly, the demand for boarding, which is issued by other users with the origin located near station a, will also be notified to station a to board. Accordingly, the traffic stop station provided by the embodiment can meet the travel demands of people, and the sharing property and convenience of traffic travel are improved.

In this embodiment, by clustering the historical trip start position and the historical trip end position in the target traffic area, at least one start cluster and at least one end cluster can be obtained; and determining a location of the transit stop within the target traffic zone based on the at least one start cluster and the at least one end cluster. Accordingly, in the embodiment of the application, the travel behaviors of the crowd are analyzed in a clustering mode, so that the travel demands of the crowd can be accurately mined, the position of the traffic stop station is determined more flexibly and reasonably, and the convenience of traffic travel is improved.

In the above or below embodiments, a plurality of first statistical periods may be determined; respectively selecting a historical travel starting position and a historical travel ending position which are positioned under each first statistical time period from the historical travel starting position and the historical travel ending position in the target traffic area; and clustering the historical travel starting position and the historical travel ending position under each first statistical time segment respectively to determine at least one starting point cluster and at least one ending point cluster of the target traffic area under each first statistical time segment, and further determine the position of the traffic stop station of the target traffic area under each first statistical time segment.

The length level of the first statistical period may be a second level, a grading level, a time level, a day level, a week level, a month level, or a quarter level, which is not limited in this embodiment. For example, the first statistical period may be 7:00-8:00, or Tuesday, or may be the month of Jute, spring, or the like.

In addition, the lengths of the different first statistics time segments may not be exactly the same. For example, one of the first statistical periods may be 7:00-8:00 and the other first statistical period may be 8:01-10:00. Typically, in the one-time stop site addressing scheme, the plurality of first statistics time segments are in uniform length level, but the embodiment is not limited thereto.

In practical application, a first statistical period to which the current time belongs can be determined; and releasing the position of the traffic stop under the first statistical time period to which the current time belongs.

Taking the time level as an example of the length level of the first statistical period, in this embodiment, 8 first statistical periods may be determined, where the first statistical periods are respectively: 7:01-8:00, 8:01-9:00, 9:01-10:00, 10:01-17:00, 17:01-18:00, 18:01-19:00, 19:01-20:00, 20:01-7:00. In this way, the natural time can be sliced into the 8 first statistical periods. In the case of ride demands, the location of the transit stop at the first statistical time period to which the current time belongs may be output in response to the ride demands.

Referring to fig. 1b, if the departure time of the user is 7:30, selecting the nearest site from the traffic stop sites in the first statistics time period of 7:01-8:00, and issuing the nearest site to the input starting point of the user to the user. Accordingly, when the departure times of the users are different, the locations of the boarding sites received by the users may be different. This may be more consistent with the travel behavior of the crowd.

Accordingly, in this embodiment, the traffic stop in the target traffic area can be dynamically adjusted following the natural time. The traffic stop station is enabled to meet the time characteristics of the travel demands of the crowd, and the travel demands of the crowd at different times can be adapted.

In the above or the following embodiments, at least one second statistical period may also be determined, where the length level of the second statistical period may be a second level, a classification level, a time level, a day level, a week level, a month level, or a quarter level, which is not limited in this embodiment. For example, the first statistical period may be 7:00-10:00 of the early peak, or may be the first day of congestion, or may be the spring of the traveling season.

In addition, the lengths of the different second statistical periods may not be exactly the same. For example, one of the second statistical periods may be 7:00-10:00, the other second statistical period may be 10:01-18:00, and so on.

In this embodiment, each of the second statistical periods may include a plurality of first statistical periods. The number, length, or level of length of the first statistical period included in each second statistical period may not be identical. Typically, in the one-time stop site addressing scheme, the plurality of first statistics time segments are in uniform length level, but the embodiment is not limited thereto.

For example, a certain second statistical period is 7:00-10:00 of early peak, and the second statistical period can be divided into three first statistical periods, 7:00-8:00, 8:01-9:00 and 9:01-10:00. The other second statistical period is 10:01-18:00, and the second statistical period can be divided into 2 first statistical periods, 10:01-14:00 and 14:01-18:00. Of course, this is merely exemplary, and the present embodiment is not limited thereto.

Based on the determined at least one second statistical period, a historical travel starting position and a historical travel ending position of at least one traffic area in each second statistical period can be obtained; and selecting N traffic areas meeting the travel point position requirements from at least one traffic area as target traffic areas according to each second statistical period, wherein N is a positive integer.

In practical application, the historical trip starting position and the historical trip ending position of at least one traffic area in each second statistical period can be obtained from trip record data corresponding to the environment area to be analyzed.

As mentioned before, the trip record data is used to record the historical trip behavior occurring within the environmental area to be analyzed. The travel record data may further include travel time information corresponding to each O, D point. Based on travel time information in the travel record data, historical travel behaviors of the environment area to be analyzed under each second statistical period can be determined, and further, for each second statistical period, a historical travel starting position and a historical travel ending position in each traffic area can be obtained. For convenience of description, the historical trip starting position and the historical trip ending position are collectively called trip points.

Accordingly, in this embodiment, N traffic areas meeting the travel point location requirement may be selected from at least one traffic area as the target traffic areas. The value of N may be set according to actual needs, and in addition, the values of N in different second statistical periods may not be identical, which is not limited in this embodiment.

In one implementation, the N traffic regions with the greatest total number of points may be selected from the at least one traffic region. Namely, N traffic areas with the largest number of travel points in the environment area to be analyzed are respectively used as target traffic areas, so that traffic stop stations in the selected N traffic areas are respectively determined.

In another implementation, N traffic regions may be selected from the at least one traffic region having a total number of points greater than a point number threshold. The number of points threshold may be set according to practical situations, for example, the number of points threshold may be 1000, and when the total number of points in the traffic area is greater than 1000, the traffic area may be determined as the target traffic area.

In yet another implementation, the N traffic regions with the greatest dot density may be selected from the at least one traffic region. Where the dot density is the ratio between the total number of pointing bits and the area of the traffic zone.

Of course, these are merely exemplary, and other point location requirements may be employed by the present embodiments to screen out a target traffic area from at least one traffic area. For example, the trip point location requirement may also be that the point location density is greater than a preset density threshold, and the embodiment is not limited thereto.

In this embodiment, N target traffic areas meeting the travel point location requirements may be screened out from the environmental area to be analyzed in different second statistical periods, so that different target traffic areas may be focused in different second statistical periods, which makes the address selection of the traffic stop more meeting the time characteristics of the travel behaviors of the crowd. For traffic areas outside the target traffic area, the traffic stop stations can be not provided, so that traffic resources can be concentrated in the target traffic area with dense crowd traveling behaviors, and the convenience of traffic traveling is improved.

In the above or below embodiments, the traffic travel categories related to the historical travel behaviors occurring in the environmental area to be analyzed are various, and for example, may be related to a bus travel category, a subway travel category, a network bus travel category, a taxi travel category, and the like.

In this embodiment, for a target traffic area, at least one traffic travel category related to a historical travel starting position and a historical travel ending position in the target traffic area may be determined; and clustering the historical travel starting position and the historical travel ending position under each traffic category respectively under each traffic category to obtain a starting point cluster and an ending point cluster under each traffic category.

At least one travel category related to the historical travel starting position and the historical travel ending position in the target traffic area may be obtained from travel record data, and the embodiment is not limited thereto.

Taking a bus trip class as an example, in the embodiment, a historical trip starting position and a historical trip ending position under the bus trip class in a target traffic area can be determined, and the historical trip starting positions under the bus trip class are clustered to obtain a starting point cluster under the bus trip class; and clustering the historical travel end positions under the bus travel class to obtain the end point cluster under the bus travel class.

Similarly, a starting point cluster and a terminal point cluster of the target traffic area under the subway trip class, a starting point cluster and a terminal point cluster of the target traffic area under the network taxi trip class or a starting point cluster and a terminal point cluster of the target traffic area under the taxi trip class can be obtained.

Based on this, the location of the transit stop under each traffic category within the target traffic area may be determined based on the start and end clusters under each traffic category, respectively.

By receiving the above examples, the positions of the traffic stop stations of the target traffic area under the bus travel class, the subway travel class, the network about car travel class and the taxi travel class can be determined respectively.

In this embodiment, the travel demands of the people under different travel categories can be fully mined by independently analyzing different travel types, so that different travel stop stations can be configured for different travel categories, and the travel demands of different people can be further satisfied.

In the above or below embodiments, based on the determined positions of the traffic stop points in the target traffic area, it may be further determined whether the euclidean distance between any traffic stop points is less than a preset distance threshold, and two traffic stop points whose euclidean distance is less than the preset distance threshold are fused.

As mentioned above, in the present embodiment, the categories of the respective traffic stops may be distinguished, or the categories of the respective traffic stops may not be distinguished.

If the categories of the traffic stations are not distinguished, any two traffic stop stations with Euclidean distances smaller than a preset distance threshold value in the target traffic area can be fused. In this case, each of the finally obtained transit stops may be used as a travel start point or a travel end point.

If the categories of the traffic stations are distinguished, the fusion of the traffic stations can be carried out in two aspects.

On the one hand, any two traffic stop departure sites with Euclidean distances smaller than a preset distance threshold and different traffic travel categories in a target traffic area can be fused, and traffic stop arrival sites with Euclidean distances smaller than the preset distance threshold and different traffic travel categories in the target traffic area can be fused. For example, if the euclidean distance between a certain traffic stop departure station under the bus travel class and a certain traffic stop departure station under the subway travel class for the target traffic area is less than 300 meters, the two traffic stop departure stations can be fused.

On the other hand, any two traffic stop stations with Euclidean distances smaller than a preset distance threshold and different belonging station categories in the target traffic area can be fused. That is, the stop departure site and the stop arrival site satisfying the requirement are merged. For example, a certain stop departure station and a certain stop arrival station within the target traffic area may be fused if the Euclidean distance between the two stations is less than 300 meters. The traffic stop stations obtained after fusion can be used for making a line start point and a line end point.

The fusion mentioned in this embodiment refers to fusion of position angles, that is, fusing the positions of two traffic stop stations with similar positions together, for example, the position of one of the traffic stop stations may be used as the position of the fused traffic stop station, or the midpoint position of the position connection line of the two traffic stop stations may be used as the position of the fused traffic stop station. It should be understood that the post-fusion transit stop has the attributes of both pre-fusion transit stops.

In this embodiment, through the integration of the traffic stop stations, the common travel demands of the people under different traffic travel categories can be integrated, so that the integrated traffic stop stations can simultaneously meet the common travel demands of the people under various traffic travel categories, and the travel demands of more people can be met through a single traffic stop station. In addition, the fusion processing under different site types can meet the demands of departure and arrival of people through a single traffic stop site.

In the above or below embodiments, in the process of clustering the historical trip starting position and the historical trip ending position in the target traffic area, the clustering parameters may be dynamically adjusted to obtain a more reasonable clustering result.

Specifically, the initial clustering parameter may be used to perform initial clustering on the historical trip starting position and the historical trip ending position to obtain at least one starting point initial cluster and at least one ending point initial cluster; if the number of clusters meeting the re-aggregation condition in the at least one starting point primary cluster and the at least one ending point primary cluster is larger than a preset number threshold, adjusting the clustering parameters until the number of clusters meeting the re-aggregation condition in the at least one starting point cluster and the at least one ending point cluster obtained after the historical trip starting position and the historical trip ending position are clustered according to the adjusted clustering parameters is smaller than the preset number threshold.

In this embodiment, the number of times of adjustment of the cluster parameters is not limited. After the clustering parameters are adjusted each time, the historical travel starting position and the historical travel ending position in the target traffic area can be clustered again, whether the clustering result meets the refocusing condition or not is determined, and if the clustering result meets the refocusing condition, the clustering parameters are adjusted again until the clustering result obtained according to the adjusted clustering parameters does not meet the refocusing condition.

In this embodiment, the refocusing condition may be set such that a ratio of the number of travel points in the cluster, whose distance from the center of the cluster meets a preset requirement, to the total number of travel points is smaller than a preset ratio threshold. Specifically, the refocusing conditions may be set as: the ratio obtained is less than 80% (the distance from the cluster center is less than 1.4, the number of trip points is less than 300 meters)/the total number of trip points in the cluster. Of course, this is merely an example, and the present embodiment is not limited thereto.

Taking the K-means algorithm as an example, after clustering the historical travel starting position and the historical travel ending position in the target traffic area according to the initial clustering parameters, the obtained clustering result accords with the condition that the obtained ratio of the result value of the distance from the center of the cluster is less than 300 meters of the number of travel points to the total number of the travel points in the cluster is less than 80 percent, and the K value in the algorithm can be increased so that the clustering result satisfies the condition that the result value of the distance from the center of the cluster is less than 300 meters of the number of travel points to the total number of the travel points in the cluster, and the obtained ratio is greater than or equal to 80 percent. Thereby acquiring at least one start cluster and at least one end cluster within the target traffic area.

In this embodiment, by setting the refocus condition, it can be ensured that the service radius of the traffic stop station determined by the specifications of the start cluster and the end cluster obtained after clustering is matched with the walking ability of the crowd, so that the traffic stop station is ensured to exist in the walking ability range of the crowd, and the convenience of the crowd in traveling can be effectively improved.

Fig. 4 is a flowchart of a method for recommending a stop for a vehicle according to another embodiment of the present application. As shown in fig. 4, the method includes:

400. receiving a travel request sent by terminal equipment, wherein the travel request comprises a starting position and a termination position;

401. selecting a target traffic stop station adapted to the start position and the end position from the at least one traffic station;

402. recommending the target traffic stop to the terminal equipment;

The method for recommending the traffic stop stations provided by the embodiment can be applied to various traffic planning scenes, and the application scenes are not limited in the embodiment.

The embodiment mainly explains the recommendation method of the traffic stop station from the server side. In this embodiment, based on the traffic stop obtained in the foregoing embodiment of the method for selecting a location of a traffic stop, a destination traffic stop adapted to a travel request of a user may be selected from at least one traffic stop according to the travel request sent by the terminal device.

In this embodiment, the selection of the target transportation stop station may be performed based on travel preferences of different users. For example, when the user prefers to be close, the nearest transit stop from the start position and the end position may be selected as the target transit stop, respectively. For another example, when the user prefers to get to the stop fast, the stop with the shortest arrival time around the start position and the end position may be selected as the target stop. For another example, when the user preference is low cost, the lowest cost transit stop around the start and end locations, respectively, may be selected as the target transit stop.

As mentioned in the previous embodiments, corresponding transit stops for the same traffic zone at different statistical times may be different.

Based on this, in this embodiment, if the travel request further includes travel time, a statistical period to which the travel time belongs may be determined; a target transit stop adapted to the start and end positions is selected from at least one transit stop under the statistical period.

This allows more accurate determination of the target transit stop adapted to the user's travel request.

In addition, in practical application, if the travel request does not include travel time, the travel time may be defaulted to be the current time. On the basis of the above, in this embodiment, the statistical period to which the current time belongs may be determined, and the target traffic stop adapted to the start position and the end position may be selected from at least one traffic stop under the statistical period to which the current time belongs.

In this embodiment, if the travel request further includes a price parameter, determining whether the price parameter meets a predetermined condition; if the price parameter meets the preset condition, the service vehicle is allocated to the target traffic stop station preferentially.

In addition, for a plurality of traffic stop stations with car collision, the total price parameter information of different traffic stop stations can be compared based on the price parameters of different users for the same traffic stop station, so that the priority of service vehicles can be allocated for setting the traffic stop stations.

Of course, these are exemplary, and the present embodiment is not limited thereto.

It should be noted that, the stop sites related to the present embodiment may be determined based on the method for selecting the stop sites, where the process for selecting the stop sites may refer to the related description in the foregoing embodiment, which is not repeated herein for saving the space, but should not cause a loss of protection scope of the present application.

Fig. 5 is a schematic flow chart of a method for recommending a stop-stop station according to another embodiment of the present application.

As shown in fig. 5, the method includes:

500. responding to a travel configuration operation of a user, and generating a travel request, wherein the travel request comprises a starting position and a termination position;

501. transmitting the travel request to a server for the server to select a target traffic stop station matched with the starting position and the ending position from at least one traffic station and recommending;

502. outputting the position of the target traffic stop recommended by the server;

The recommendation method of the traffic stop station provided by the embodiment can be applied to various traffic planning scenes, and the application scenes are not limited by the embodiment.

The embodiment mainly explains the recommendation method of the traffic stop station from the terminal equipment side. In this embodiment, the terminal device may provide a human-computer interaction interface for the user. For example, a human-computer interaction interface is shown in fig. 1b, and the present embodiment is not limited to the human-computer interaction interface shown in fig. 1 b.

The user can execute travel configuration operation in the man-machine interaction interface, and input the starting position and the ending position of the travel. The terminal device can generate a travel request according to the travel request, and send the travel request to the server.

And under the condition that the server receives the travel request, selecting a target traffic stop station matched with the starting position and the ending position from at least one traffic station, and feeding back the target traffic stop station to the terminal equipment as a recommended result.

The terminal device can display the position of the target traffic stop in the man-machine interaction interface. The location of the target transportation stop station can be shown in the map.

For example, the station a in fig. 1b is a target traffic stop station fed back by the server according to the starting position and the ending position input by the user.

In addition, in this embodiment, the user may also input information such as trip time and/or price parameters in the man-machine interaction interface. The terminal device may configure this information into the travel request to provide this information to the server.

The server can then select the destination traffic station based on the information. The process of selecting the target traffic station in the server may refer to the embodiment of the recommended method of the traffic stop set forth in the server side, which is not described herein.

It should be noted that, the traffic stop points related to the present embodiment may be determined based on the foregoing method for selecting the address of the traffic stop point, where the process of selecting the address of the traffic stop point may refer to the related description in the foregoing embodiment, and in addition, the selection operation of the target traffic stop point by the server may refer to the foregoing embodiment of the recommended method of the traffic stop point, which is not repeated herein for saving space, but should not cause loss of protection scope of the present application.

It should be noted that, the execution subjects of each step of the method provided in the above embodiment may be the same device, or the method may also be executed by different devices. For example, the execution subject of steps 101 to 100 may be device a; for another example, the execution subject of

steps

101 and 100 may be device a, and the execution subject of step 102 may be device B; etc.

In addition, in some of the flows described in the above embodiments and the drawings, a plurality of operations appearing in a specific order are included, but it should be clearly understood that the operations may be performed out of the order in which they appear herein or performed in parallel, the sequence numbers of the operations such as 101, 100, etc. are merely used to distinguish between the various operations, and the sequence numbers themselves do not represent any order of execution. In addition, the flows may include more or fewer operations, and the operations may be performed sequentially or in parallel. It should be noted that, the descriptions of "first" and "second" herein are used to distinguish different messages, devices, modules, etc., and do not represent a sequence, and are not limited to the "first" and the "second" being different types.

Fig. 6 is a schematic structural diagram of a computing device according to another embodiment of the present application. As shown in fig. 6, the computing device may include: a memory 60 and a processor 61.

A processor 61 coupled to the memory 60 for executing the computer program in the memory 60 for:

the location of the transit stop within the target traffic zone is determined based on the at least one start cluster and the at least one end cluster.

In an alternative embodiment, the processor 61 is configured to, when clustering the historical trip start location and the historical trip end location respectively:

determining a plurality of first statistical periods;

respectively selecting a historical travel starting position and a historical travel ending position which are positioned under each first statistical time period from the historical travel starting position and the historical travel ending position in the target traffic area;

and clustering the historical trip starting position and the historical trip ending position under each first statistical time segment respectively to determine at least one starting point cluster and at least one ending point cluster of the target traffic area under each first statistical time segment.

In an alternative embodiment, processor 61 is further configured to:

determining a first statistical period to which the current time belongs;

and releasing the position of the traffic stop under the first statistical time period to which the current time belongs.

In an alternative embodiment, the processor 61 is further configured to, prior to acquiring the historical trip start location and the historical trip end location within the target traffic zone:

determining at least one second statistical period, each second statistical period comprising a plurality of first statistical periods;

acquiring a historical travel starting position and a historical travel ending position of at least one traffic area in each second statistical period;

and selecting N traffic areas meeting the travel point position requirements from at least one traffic area as target traffic areas according to each second statistical period, wherein N is a positive integer.

In an alternative embodiment, processor 61 is configured to, when selecting N traffic areas from the at least one traffic area that meet the travel point location requirement:

selecting N traffic areas with the maximum total number of the points from at least one traffic area; or alternatively, the process may be performed,

selecting N traffic areas with the total number of the points greater than a point number threshold value from at least one traffic area; or alternatively, the process may be performed,

N traffic regions with the highest point density are selected from at least one traffic region.

In an alternative embodiment, the first statistical period has a length level of seconds, scales, hours, days, weeks, months, or quarters; the second statistical period is of a second, graded, time, day, week, month or quarter level in length.

In an alternative embodiment, the processor 61 is configured to, when clustering the historical trip start location and the historical trip end location to obtain at least one start cluster and at least one end cluster, respectively:

determining at least one traffic travel category related to the historical travel starting position and the historical travel ending position;

clustering the historical travel starting positions and the historical travel ending positions under the traffic categories respectively under each traffic category to obtain a starting point cluster and an ending point cluster under each traffic category;

determining a location of a transit stop within a target traffic zone based on at least one start cluster and at least one end cluster, comprising:

and respectively determining the positions of the traffic stop sites in each traffic category in the target traffic area based on the starting point cluster and the ending point cluster in each traffic category.

In an alternative embodiment, processor 61, when clustering the historical trip start locations and the historical trip end locations to obtain at least one start cluster and at least one end cluster, is configured to:

performing preliminary clustering on the historical trip starting position and the historical trip ending position according to the initial clustering parameters to obtain at least one starting point preliminary cluster and at least one ending point preliminary cluster;

if the number of clusters meeting the re-aggregation condition in the at least one initial point primary cluster and the at least one final point primary cluster is larger than a preset number threshold value, then

And adjusting the clustering parameters until the number of clusters meeting the re-aggregation condition in at least one starting point cluster and at least one ending point cluster obtained after the historical trip starting position and the historical trip ending position are clustered according to the adjusted clustering parameters is smaller than a preset number threshold.

In an alternative embodiment, the re-aggregation condition is that the ratio of the number of trip points in the cluster to the total number of trip points, the distance from the center of the cluster meeting a preset requirement, is smaller than a preset ratio threshold.

In an alternative embodiment, processor 61, when determining the location of the transit stop within the target traffic zone based on the at least one start cluster and the at least one end cluster, is configured to:

Determining a traffic stop departure station in the target traffic area according to at least one starting point cluster;

and determining that the traffic stops in the target traffic area reach the station according to the at least one end point cluster.

In an alternative embodiment, processor 61, when determining a transit departure point within the target traffic area based on the at least one origin cluster, is configured to:

for a first cluster in at least one starting cluster, if a known traffic stop station exists in the coverage area of the first cluster, selecting one of the known traffic stop stations as a traffic stop departure station in the coverage area of the first cluster;

if the known traffic stop stations do not exist in the area covered by the first cluster, determining the traffic stop departure stations of the area covered by the first cluster according to the cluster center of the first cluster;

wherein the first cluster is any one of the at least one starting cluster.

In an alternative embodiment, the processor 61, when executing the selecting one of the known transit stops as the transit stop departure stop of the area covered by the first cluster if the known transit stop exists in the area covered by the first cluster, is configured to:

If a plurality of known traffic stop stations exist in the coverage area of the first cluster, the known traffic stop station closest to the cluster center is taken as the traffic stop departure station of the coverage area of the first cluster;

and if one traffic stop station exists in the coverage area of the first cluster, taking the known traffic stop station as a traffic stop departure station in the coverage area of the first cluster.

In an alternative embodiment, the processor 61, when executing the determination of the transit departure point of the area covered by the first cluster from the cluster center of the first cluster if there is no known transit point within the area covered by the first cluster, is configured to:

if the known traffic stop stations do not exist in the coverage area of the first cluster, setting a traffic stop departure station at the central position of the first cluster; or alternatively, the process may be performed,

the known transit stop closest to the center of the cluster is taken as the transit stop departure stop in the area covered by the first cluster.

In an alternative embodiment, the processor 61, when determining that a stop within the target traffic area arrives at a stop based on at least one end cluster, is configured to:

for a second cluster in the at least one destination cluster, if a known traffic stop station exists in the coverage area of the second cluster, selecting one of the known traffic stop stations as a traffic stop arrival station in the coverage area of the second cluster;

If the known traffic stop stations do not exist in the area covered by the second cluster, determining that the traffic stops of the area covered by the second cluster reach the stations according to the cluster center of the second cluster;

wherein the second cluster is any one of the at least one end-point cluster.

In an alternative embodiment, the processor 61, when executing if there is a known transit stop in the coverage area of the second cluster, is configured to select one of the known transit stop as a transit stop arrival stop in the coverage area of the second cluster:

if a plurality of known traffic stop stations exist in the coverage area of the second cluster, the known traffic stop station closest to the cluster center is taken as the traffic stop arrival station of the coverage area of the second cluster;

and if one traffic stop station exists in the coverage area of the second cluster, taking the known traffic stop station as a traffic stop arrival station of the coverage area of the second cluster.

In an alternative embodiment, the processor 61, when executing the determination that the traffic stop of the area covered by the second cluster arrives at the station based on the cluster center of the second cluster if there is no known traffic stop station in the area covered by the second cluster, is configured to:

If the second cluster is covered by the area where the known traffic stop stations do not exist, setting up traffic stop arrival stations at the central position of the second cluster; or alternatively, the process may be performed,

the known transit stop closest to the center of its cluster is taken as the transit stop arrival stop within the area covered by the second cluster.

In an alternative embodiment, processor 61 is further configured to:

if two traffic stop stations with Euclidean distance smaller than a preset distance threshold exist in the target traffic area, the two traffic stop stations are fused.

Further, as shown in fig. 6, the computing device further includes: communication component 62, power supply component 63, and the like. Only some of the components are schematically shown in fig. 6, which does not mean that the computing device only includes the components shown in fig. 6.

Wherein the power supply assembly 63 provides power to various components of the device in which the power supply assembly is located. The power components may include a power management system, one or more power sources, and other components associated with generating, managing, and distributing power for the devices in which the power components are located.

It should be noted that, for the technical details related to the embodiments of the computing device, reference may be made to the related descriptions in the embodiments of the method for locating a stop for transportation, which are not repeated here for the sake of brevity. But this should not result in a loss of scope of protection for the present application.

Accordingly, embodiments of the present application also provide a computer-readable storage medium storing a computer program that, when executed, is capable of implementing the steps of the method embodiments described above that may be performed by a computing device.

Fig. 7 is a schematic structural diagram of another computing device according to another embodiment of the present application. As shown in fig. 7, the computing device may include: a memory 70, a processor 71 and a communication component 72.

A processor 71 coupled with the memory 70 and the communication component 72 for executing the computer program in the memory 70 for:

receiving a travel request sent by the terminal equipment through the communication component 72, wherein the travel request comprises a starting position and a termination position;

selecting a target traffic stop station adapted to the start position and the end position from the at least one traffic station;

recommending the target transportation stop to the terminal device through the communication component 72;

In an alternative embodiment, processor 71 is further configured to:

if the travel request also comprises travel time, determining a statistical period to which the travel time belongs;

The processor is configured to, when selecting a target transit stop adapted to a start location and an end location from at least one transit stop:

a target transit stop adapted to the start and end positions is selected from at least one transit stop under the statistical period.

In an alternative embodiment, processor 71 is further configured to:

if the travel request also comprises price parameters, judging whether the price parameters meet preset conditions or not;

and under the condition that the price parameter meets the preset condition, allocating the service vehicle for the target transportation stop preferentially.

Further, as shown in fig. 7, the computing device further includes: power supply assembly 73, and the like. Only some of the components are schematically shown in fig. 7, which does not mean that the computing device only includes the components shown in fig. 7.

It should be noted that, for the technical details related to the embodiments of the computing device, reference may be made to the related description in the embodiments of the recommended method related to the stop-and-go station, which is not repeated herein for the sake of brevity. But this should not result in a loss of scope of protection for the present application.

Fig. 8 is a schematic structural diagram of a terminal device according to another embodiment of the present application. As shown in fig. 8, the computing device may include: a memory 80, a processor 81 and a communication component 82.

A processor 81 coupled with the memory 80 and the communication component 82 for executing the computer program in the memory 80 for:

transmitting the travel request to the server through the communication component 82 for the server to select and recommend a target transit stop adapted to the start and end locations from the at least one transit stop;

outputting the position of the target traffic stop recommended by the server;

In an alternative embodiment, the travel request further includes travel time and/or price parameters.

Further, as shown in fig. 8, the terminal device further includes: power supply assembly 83, display 84, audio assembly 85, and other components. Only part of the components are schematically shown in fig. 8, which does not mean that the terminal device only comprises the components shown in fig. 8.

It should be noted that, for the technical details related to the embodiment of the terminal device, reference may be made to the related description in the embodiment of the recommended method related to the stop-and-go station, which is not repeated herein for the sake of brevity. But this should not result in a loss of scope of protection for the present application.

Accordingly, the present application further provides a computer readable storage medium storing a computer program, where the computer program is executed to implement the steps executable by the terminal device in the above method embodiments.

The memory of fig. 6-8, among other things, is used to store computer programs and may be configured to store various other data to support operations on a computing device. Examples of such data include instructions for any application or method operating on a computing device, contact data, phonebook data, messages, pictures, videos, and the like. The memory may be implemented by any type of volatile or nonvolatile memory device or combination thereof, such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disk.

Wherein the communication assembly of fig. 6-8 is configured to facilitate wired or wireless communication between the device in which the communication assembly is located and other devices. The device in which the communication component is located may access a wireless network based on a communication standard, such as WiFi,2G or 3G, or a combination thereof. In one exemplary embodiment, the communication component receives a broadcast signal or broadcast-related information from an external broadcast management system via a broadcast channel. In one exemplary embodiment, the communication component may be implemented based on Near Field Communication (NFC) technology, radio Frequency Identification (RFID) technology, infrared data association (IrDA) technology, ultra Wideband (UWB) technology, bluetooth (BT) technology, or other technologies to facilitate short range communications.

Among them, the display in fig. 8 includes a screen, which may include a Liquid Crystal Display (LCD) and a Touch Panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive input signals from a user. The touch panel includes one or more touch sensors to sense touches, swipes, and gestures on the touch panel. The touch sensor may sense not only the boundary of a touch or slide action, but also the duration and pressure associated with the touch or slide operation.

Wherein the audio component of fig. 8 may be configured to output and/or input audio signals. For example, the audio component includes a Microphone (MIC) configured to receive external audio signals when the device in which the audio component is located is in an operational mode, such as a call mode, a recording mode, and a speech recognition mode. The received audio signal may be further stored in a memory or transmitted via a communication component. In some embodiments, the audio assembly further comprises a speaker for outputting audio signals.

It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

In one typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.

The memory may include volatile memory in a computer-readable medium, random Access Memory (RAM) and/or nonvolatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of computer-readable media.

Computer readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of storage media for a computer include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information that can be accessed by a computing device. Computer-readable media, as defined herein, does not include transitory computer-readable media (transmission media), such as modulated data signals and carrier waves.

It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article or apparatus that comprises the element.

The foregoing is merely exemplary of the present application and is not intended to limit the present application. Various modifications and changes may be made to the present application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc. which are within the spirit and principles of the present application are intended to be included within the scope of the claims of the present application.

Claims

1. A method of locating a transit stop comprising:

determining a location of a transit stop within the target traffic zone based on the at least one start cluster and at least one end cluster;

the determining a location of a transit stop within the target traffic area based on the at least one start cluster and at least one end cluster comprises: if the area covered by any one of the at least one starting point cluster and the at least one ending point cluster does not have the known traffic stop, determining the traffic stop of the area covered by the any one cluster according to the cluster center of the any one cluster.

2. The method of claim 1, wherein clustering the historical trip start location and the historical trip end location to obtain at least one start cluster and at least one end cluster, respectively, comprises:

determining a plurality of first statistical periods;

3. The method as recited in claim 2, further comprising:

determining a first statistical period to which the current time belongs;

4. The method of claim 2, further comprising, prior to acquiring the historical trip start location and the historical trip end location within the target traffic zone:

Determining at least one second statistical period, each second statistical period comprising the plurality of first statistical periods;

and selecting N traffic areas meeting travel point position requirements from the at least one traffic area as the target traffic areas according to each second statistical period, wherein N is a positive integer.

5. The method of claim 4, wherein the selecting N traffic areas from the at least one traffic area that meet travel point location requirements comprises:

selecting N traffic areas with the maximum total number of the points from the at least one traffic area; or alternatively, the process may be performed,

selecting N traffic areas with the total number of the points greater than a point number threshold value from the at least one traffic area; or alternatively, the process may be performed,

and selecting N traffic areas with the maximum point density from the at least one traffic area.

6. The method of claim 4, wherein the first statistical period of time is on the order of seconds, scales, hours, days, weeks, months, or quarters; the length level of the second statistical period is second level, grading, time level, day level, week level, month level or quarter level.

7. The method of claim 1, wherein clustering the historical trip start locations and the historical trip end locations to obtain at least one start cluster and at least one end cluster, respectively, comprises:

clustering the historical travel starting positions and the historical travel ending positions under each traffic category respectively under each traffic category to obtain a starting point cluster and an ending point cluster under each traffic category;

the determining a location of a transit stop within the target traffic area based on the at least one start cluster and at least one end cluster comprises:

and respectively determining the positions of the traffic stop sites under each traffic class in the target traffic area based on the starting point cluster and the ending point cluster under each traffic class.

8. The method of claim 1, wherein clustering the historical trip start locations and the historical trip end locations to obtain at least one start cluster and at least one end cluster comprises:

Performing preliminary clustering on the historical trip starting position and the historical trip ending position according to initial clustering parameters to obtain at least one starting point preliminary cluster and at least one ending point preliminary cluster;

And adjusting the clustering parameters until the number of clusters meeting the re-aggregation condition in at least one starting point cluster and at least one ending point cluster obtained after the historical trip starting position and the historical trip ending position are clustered according to the adjusted clustering parameters is smaller than the preset number threshold.

9. The method of claim 8, wherein the re-aggregation condition is that a ratio of a number of trip points in the cluster to a total number of trip points, the distance from a center of the cluster satisfying a preset requirement, is less than a preset ratio threshold.

10. The method of claim 1, wherein if there is no known transit stop in the area covered by any one of the at least one starting cluster, determining a transit stop departure point in the area covered by the any one cluster according to the cluster center of the any one cluster;

If the known traffic stop station does not exist in the area covered by any one of the at least one end point cluster, determining that the traffic stop of the area covered by the any one cluster arrives at the station according to the cluster center of the any one cluster.

11. The method of claim 10, wherein the determining the location of the transit stop within the target traffic zone based on the at least one start cluster and at least one end cluster further comprises:

and if the known traffic stop stations exist in the coverage area of any one of the at least one starting point cluster and the at least one ending point cluster, selecting one of the known traffic stop stations as the traffic stop station of the coverage area of the any one cluster.

12. The method of claim 11, wherein selecting one of the known transit stops as the transit stop departure stop for the area covered by any one of the at least one start cluster and the at least one end cluster if the known transit stop exists in the area covered by the any one of the at least one start cluster and the at least one end cluster comprises:

If a plurality of known traffic stop stations exist in the coverage area of any one cluster, the known traffic stop station closest to the cluster center is used as the traffic stop station of the coverage area of any one cluster;

and if one traffic stop station exists in the coverage area of any one cluster, taking the known traffic stop station as the traffic stop station of the coverage area of any one cluster.

13. The method of claim 1, wherein the determining the transit stop for the area covered by the any one cluster based on the cluster center of the any one cluster comprises:

setting up the traffic stop station at the central position of the cluster; or alternatively, the process may be performed,

and taking the known traffic stop closest to the center of the cluster as the traffic stop in the area covered by any cluster.

14. The method according to any one of claims 1 to 13, further comprising:

and if two traffic stop stations with the Euclidean distance smaller than the preset distance threshold exist in the target traffic area, fusing the two traffic stop stations.

15. A method of recommending a transit stop, comprising:

recommending the target traffic stop to the terminal equipment;

the at least one traffic stop station is determined by respectively clustering the historical trip starting position and the historical trip ending position by the server to obtain at least one starting point cluster and at least one ending point cluster; the server determining the location of the transit stop comprises: if the area covered by any one of the at least one starting point cluster and the at least one ending point cluster does not have the known traffic stop, determining the traffic stop of the area covered by the any one cluster according to the cluster center of the any one cluster.

16. The method as recited in claim 15, further comprising:

the selecting a target traffic stop station adapted to the starting position and the ending position from at least one traffic station comprises:

A target transit stop station adapted to the starting position and the ending position is selected from at least one transit stop station under the statistical period.

17. The method as recited in claim 15, further comprising:

and under the condition that the price parameter meets the preset condition, allocating service vehicles for the target transportation stop station preferentially.

18. A method of recommending a transit stop, comprising:

the travel request is sent to a server, so that the server can select a target traffic stop station matched with the starting position and the ending position from at least one traffic station and recommend the target traffic stop station;

outputting the position of the target transportation stop recommended by the server;

the method for determining the position of the traffic stop station by the server comprises the following steps of: if the area covered by any one of the at least one starting point cluster and the at least one ending point cluster does not have the known traffic stop, determining the traffic stop of the area covered by the any one cluster according to the cluster center of the any one cluster.

19. The method of claim 18, wherein the travel request further comprises travel time and/or price parameters.

20. A computing device comprising a memory and a processor;

the memory is used for storing one or more computer instructions;

21. A computing device comprising a memory, a communication component, and a processor;

the memory is used for storing one or more computer instructions;

22. A terminal device comprising a memory, a communication component, and a processor;

the memory is used for storing one or more computer instructions;

23. A computer-readable storage medium storing computer instructions that, when executed by one or more processors, cause the one or more processors to perform the method of locating a transit stop as claimed in any one of claims 1-14 or the method of recommending a transit stop as claimed in any one of claims 15-19.